1. Field of the Invention
The present invention relates to a method and a system for supporting decision-making.
2. Description of the Prior Art
A decision-making support system now available on the market is "EXCEED". This system is capable of processing various table type data into a new column or row data, presenting a table type data in chart form, and searching for and displaying specific data on the screen. The user is in a position to designate these procedures sequentially. Also, the order of processing may be registered in the system as a command file in advance. This makes it possible to display and present to the user information considered effective in advance. It is also of course possible to have a dialogue with the system to search for or process data as required.
The present invention is also required to be studied from the viewpoint of a method of knowledge processing, and therefore explanation will be made below about a conventional method of the knowledge processing.
In a system for describing the knowhow of an expert in the form of knowledge presentation of a rule or the like, storing it in a knowledge base and utilizing it for various decisions or analyses, the knowledge stored in the knowledge base is required to be reasonable. The
evaluation for this purpose requires a task called knowledge regulation. An expert system structuring tool marketed now is such that this task is performed in such a manner that a hypothetical test case is inputted manually and the resultant output is examined manually, and if the result is undesirable, the case is traced to correct corresponding knowledge. An "ES/KERNEL" is Hitachi's conventional expert system structuring tool. According to the ES/KERNEL, data accessed by a rule is stored in a data storage area called a frame. Further, there is an area called a slot in the frame for storing individual data items. An arrangement may be used as a type of this slot.
Furthermore, a support system for the dealing task in the financial industry includes a "Market Mind". This system, while monitoring the fluctuations of stock prices of various descriptions of stock, gives an alarm as information whether a given description of stock rises or falls in price on the basis of the knowhow presented by the rule.
The conventional methods, however, have the problem described below.
The existing decision-making support systems are incapable of incorporating any knowhow of the decision-making person on the interpretation of data such as how a table type data should be interpreted or what should be presented to the user as a conclusion of interpretation.
Also, the conventional knowledge processing systems do not have any function to efficiently evaluate whether the knowhow stored in a knowledge base is reasonable. Nor are they capable of describing a rule for effectively referring to a table type data. Specifically, in the case where a column (or a row) is stored as a frame, the information on the sequential relationship of the column (or the row) is lost, so that a rule cannot be referred to when a table is stored as an arrangement of frame slots.
Also, the conventional dealing task support systems, which are adapted to output the result of execution of a reasoning as information on whether a given stock price rises or falls, are incapable of evaluating the stored knowledge to check the reasonability thereof.
As explained above, the problem of the conventional methods lie in that no consideration is given to a mechanism for structuring a decision-making support system incorporating a knowhow, or more specifically, a system for applying the knowhow to a table type data.
On the other hand, there is a decision-making support system described below for position control of the dealer to conduct financial trading with a self-position. (a financial trading held by himself).
Generally, a method of supporting the determination of the optimum processing, behavior or operation includes a technique called the linear optimization method, the nonlinear optimization method and the combinational optimization method. According to the conventional nonlinear optimization method, as discussed in "Optimization", Information Science 19, Iwanami Shoten Lecture Series, pp. 61 to 77, for example, values x.sub.1, x.sub.2, . . . , x.sub.n minimizing an objective function f (x.sub.1, x.sub.2, . . . , x.sub.n) under a constraint g.sub.i (x.sub.1, x.sub.2, . . . , x.sub.n) .ltoreq.0 are determined.
Now explanation will be made about a method of supporting the determination of an outline of option trading, which is one of the financial tradings, and an optimum trading.
The market participants in option trading conducted over the counter include a market maker in a position to supply an option as a commodity and an investor for creating the demand for an option to achieve his investment target (objective).
The task of a dealer which is a market maker is divided into the operational task for over-the-counter trading and the revenue management task for self-position (trading held by the dealer). The former includes the setting of the price of bond-option which trades over the counter and the acceptance of an order from customers (mainly investors). The latter is to decide an operational policy of the self-position and, by trading with a correspondent as required, to constantly recompile the contents of the self-position subjected to fluctuations due to the acceptance of customer orders, change in bond price or time decay (change in profit or loss with time) in conformity with the operational policy.
Specifically, the decision on the operational policy is to determine the style of the payoff function of the self-position in such a manner as to earn a profit in accordance with the move of the market price. Such a style is defined by the payoff function and the values of delta, gamma, theta or the like making up a differential function thereof for a certain value assumed by the environmental parameter (the bond price, volatility or the risk-free rate determined by the market trend) providing a part of the parameters of the payoff function. To recompile the contents of the self-position in conformity with the operational policy is to determine the contents of trading (type of option, strike price and the expiration required for satisfying a target of position tuning as a characteristic value including the payoff value, delta value, gamma value or the theta value as well as the value of the environmental parameter determined as an operational policy,) and to conduct the particular trading.
On the other hand, the investor employs an investment strategy with various styles of payoff function by changing each of the long and short calls, long and short puts and the combination ratio therebetween (type of options of call and put), strike price and the time of maturity.
Conventional option trading support systems, by contrast, as seen in the OTT (Option Trader Training) system of Intelligence Technology Co., Ltd. or the option trading (analysis) system of Japan Unysis Co., Ltd., have such simulation and analytical functions as supporting the calculation of the theoretical price of option, volatility analysis (fluctuation rate of bond price), time decay analysis and the selection of investment strategies from among the existing ones.
Also, a conventional method of option trading support in which the constraint logic programming is applied to the option trading is disclosed in IEEE Expert, Special Issue on Financial Software, August 1987, pp. 42-50. According to this method, if parts of parameters on option trading including the type of trading, the short or long call, bond price, strike price, the expiration, the coupon, the volatility, the risk-free rate, the payoff value, the delta value, the gamma value or the theta value is restricted by the user, the system is capable of responding with a value that can be taken by the remaining independent parameters. This system adopts a method in which reference is made in advance to a table registered with the value of a parameter satisfying the related equation (such as a payoff function) of parameter on the option trading, and a restrained parameter is propagated to a key and the constraint to the remaining independent parameters.
Nevertheless, a problem is posed by the conventional method as will be described. Specifically, in view of the fact that a market maker manages the revenue of the self-position, the function is lacking of supporting the trading decision for restructuring the contents of the self-position in conformity with the operational policy. The problem has been that the calculation of the option price or the volatility is for supporting the operation of the over-the-counter trading of a dealer, and the time decay analysis in a given transaction or the function for supporting the selection of one of the existing strategies, though oriented for the investors lacking the self-position, is not aimed at the dealers.
Also, a method using a constraint logic programming applied to the support of the position management task of a dealer may be utilized for determining the contents of the trading satisfying the target of position tuning coincidental with the contents of the operational policy given for an environmental parameter and a characteristic value. Specifically, an environmental parameter (the bond price, volatility or risk-free rate determined by the market trend) and the characteristic value (such values as payoff, delta, gamma, and theta) may be restrained to tuned position target thereby to determine a parameter (type of option, strike price, the expiration or the like determined by the user) representing the contents of the trading satisfying the restraint of the characteristic value and the environmental parameter. In this case, the problem has been posed that a table data is required to be registered as described above for all the combinations available for the parameters relating to these option tradings.
Another problem has been that in supporting the decision on an optimum trading parameter by a common optimization method, it is necessary to convert the difference between the style of a payoff function of the position suited to the operational policy and that of the payoff function for the position for which the trading has already been executed, into an objective function.
Still another problem has been that even if the above-mentioned objective function has been set, an increased number of trading parameters would require a longer time for optimization.